Ionic liquid ultrasound assisted dispersive liquid-liquid microextraction method for preconcentration of trace amounts of rhodium prior to flame atomic absorption spectrometry determination

In this article, we consider ionic liquid based ultrasound-assisted dispersive liquid-liquid microextraction of trace amounts of rhodium from aqueous samples and show that this is a fast and reliable sample pre-treatment for the determination of rhodium ions by flame atomic absorption spectrometry. The Rh(III) was transferred into its complex with 2-(5-bromo-2-pyridylazo)-5-diethylamino phenol as a chelating agent, and an ultrasonic bath with the ionic liquid, 1-octyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide at room temperature was used to extract the analyte. The centrifuged rhodium complex was then enriched in the form of ionic liquid droplets and prior to its analysis by flame atomic absorption spectrometry, 300 μL ethanol was added to the ionic liquid-rich phase. Finally, the influence of various parameters on the recovery of Rh(III) was optimized. Under optimum conditions, the calibration graph was linear in the range of 4.0-500.0 ng mL(-1), the detection limit was 0.37 ng mL(-1) (3S(b)/m, n = 7) and the relative standard deviation was ±1.63% (n = 7, C = 200 ng mL(-1)). The results show that ionic liquid based ultrasound assisted dispersive liquid-liquid microextraction, combined with flame atomic absorption spectrometry, is a rapid, simple, sensitive and efficient analytical method for the separation and determination of trace amounts of Rh(III) ions with minimum organic solvent consumption.     

Microwave-induced combustion process variables for MgO nanoparticle synthesis using polyethylene glycol and sorbitol

In this study, MgO nanoparticles were prepared by microwave-induced combustion synthesis of magnesium nitrate (as oxidant and MgO precursor) and polyethylene glycol and sorbitol as fuels. The effects of various parameters including the aging time of the precursor gel before combustion, microwave power and fuel-to-oxidant ratio were investigated. Microwave was applied to homogeneously heat the precursor gel. The temperature profile and the composition of the released gases during the combustion process and the carbonaceous deposits on the MgO nanoparticles were studied by FTIR, TGA, Raman spectroscopy, and temperature programmed oxidation (TPO). The MgO samples were calcined at 400 °C for 3 h and characterized using SEM, TEM, BET and PXRD. MgO nanoparticles as small as 4.1 nm were formed using 20% excess of sorbitol and 40% excess of polyethylene glycol as the fuels.     

Synthesis of cactus-like zincoxysulfide (ZnOxS1−x) nanostructures assisted by a task-specific ionic liquid and their photocatalytic activities

A hydrothermal method has been employed to prepare cactus-like zincoxysulfide ZnO_xS_1?x nanostructures with the assistance of a dicationic task-specific ionic liquid (TSIL), [mim]{(CH)₂}₃[imm](SCN)₂. To the best of our knowledge, this is the first time that this TSIL with the SCN anion has been used in place of conventional reagents as a source of S to prepare a ZnO_xS_1?x nanostructure. The photocatalytic activities of the ZnO_xS_1?x nanostructures have been compared using UV and visible lights. BET results showed that the surface areas and photocatalytic activities of cactus-like zincoxysulfide ZnO_xS_1?x nanostructures were higher than those of other samples. ZnO_xS_1?x nanostructures with cactus-like morphology exhibited a significant enhancement of photocatalytic activity toward the degradation of methyl orange (MO) as compared to other samples, as revealed by photoluminescence measurements. This could be attributed to enhanced oxygen vacancies and crystallite defects formed as a result of substitution of S^2? in the lattice of ZnO.     

Numerical Modeling of the Freezing of a Porous Humid Food inside a Cavity due to Natural Convection

The conjugate heat transfer problem of food freezing inside a cavity was numerically investigated. A vegetable sponge has been considered as a food block freezing inside a square freezing chamber due to natural convection. The need for specifying the block surface convective heat transfer coefficients was eliminated by solving the surrounding cooling fluid and, therefore, a comprehensive understanding on heat transfer and airflow during freezing can be achieved. The 2-D unsteady Navier-Stokes and energy equations were solved using a finite volume method with the semi-implicit SIMPLE algorithm. Thermophysical properties of food block components were considered to be dependent on temperature, as well as moisture and ice content, which has been rarely considered in food freezing studies. The specific heat capacity method was employed to model the freezing process. The Krischer model was adopted for predicting the thermal conductivity of the food, which indicates that the model works with reasonable accuracy for humid porous foods. The mechanism of natural convection in the cavity was carefully studied and the effects of different parameters on the freezing time were examined. The food freezing curves were investigated for various Rayleigh numbers in the range of 10⁴ ≤ Ra ≤ 10⁶, with different area ratios of A = 1/16, 1/9, and 1/4, and food initial water contents of X _tw  = 0.48, 0.58, and 0.68. It was concluded that increasing the Rayleigh number reduces the freezing time. On the other hand, area ratio and initial water content of the food were proved to extend the freezing time.     

Synthesis,characterization, and measurement of structural,optical, and phtotoluminescent properties of zinc sulfide quantum dots

A facile and rapid microwave irradiation method was developed to prepare ZnS nanoparticles (NPs) using a set of ionic liquids (ILs) based on the bis(trifluoromethylsulfonyl) imide anion and different cations of 1-alkyl-3-methyl-imidazolium. The phases, structures, and optical absorption properties of the NPs were determined in depth with X-ray powder diffraction (XRD), transmission electron microscopy (TEM), Raman spectroscopy, UV–vis absorption spectroscopy (UV–vis), diffuse reflectance spectroscopy (DRS), and photoluminescence spectroscopy (PL). The average crystallite size of the ZnS NPs calculated from the XRD pattern was of the order of 2.8 nm which exhibits cubic zinc blende structure. The energy band gap measurements of NPs were carried out by UV and DRS. The results revealed that the ZnS NPs exhibit strong quantum confinement effect. The optical band gap energy increases significantly compared with those of the bulk ZnS. The refractive indices for different ZnS nanosamples and different concentrations of ZnS NPs for a typical sample suspended in deionized water were also measured.     

Power management in SMAC-based energy-harvesting wireless sensor networks using queuing analysis

One of the most important constraints in traditional wireless sensor networks is the limited amount of energy available at each sensor node. The energy consumption is mainly determined by the choice of media access mechanism. SMAC is a typical access mechanism that has drawn much attention in recent years. In WSNs, sensors are usually equipped with capacity-limited battery sources that can sustain longer or shorter period, depending on the energy usage pattern and the activeness level of sensor nodes. To extend the lifetime of the sensor networks, ambient energy resources have been recently exploited in WSNs. Even though solar radiation is known as the superior candidate, its density varies over time depending on many factors such as solar intensity and cloud states, which makes it difficult to predict and utilize the energy efficiently. As a result, how to design an efficient MAC in a solar energy harvesting based WSN becomes a challenging problem. In this paper, we first incorporate a solar energy-harvesting model into SMAC and conduct its performance analysis from a theoretical aspect. Our research works provide a fundamental guideline to design efficient MAC for energy harvesting based WSNs. Our major contribution includes three folders: firstly, we model solar energy harvesting in a photovoltaic cell and then derive the throughput of SMAC in the energy-harvesting based WSNs. Second, we develop a new model based on queuing theory to calculate the average number of energy packets in battery in terms of both duty cycle and throughput. Finally, we form an optimization problem to find a suitable range for the duty cycle to satisfy both quality of service (QoS) and network lifetime requirements.